Firms that use remote monitoring and diagnostic systems, for example, remote water monitoring and diagnostic systems, typically have a need to create a model of the particular assets being monitored. The number of assets and the type of assets may differ. Moreover, from site to site or even within a single site, similar assets may differ from each other. As such, the structure of assets built into the model may not always be perfect. For example, an asset at one site may have more or less sensor parameters that a similar asset at another site. Sometimes even assets within a site have differing parameters. Whether due to imperfect information, differences in physical installations, differences in specifications or malfunctioning equipment, the attributes of similar assets are rarely constant. Because of such differences, using a model for performance monitoring or maintenance calculations may yield less than perfect results.
In such an environment, it is difficult to apply standard analytics to run against a fleet of assets. Often, this results in a large number of customized analytics being created, adding costs and inefficiencies to the remote monitoring of multiple sites. This also is problematic when attempting to compare similar calculated quantities across the fleet.